exitvalue-mcp

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Get M&A multiples trend by year

get_multiples_trend

Read-onlyIdempotent

Track how EV/EBITDA or EV/Revenue multiples for one industry sub-vertical changed year by year from 2018–2026, with medians, interquartile ranges and deal counts, and see missing years as gaps.

Instructions

Read-only. Year-by-year history for ONE sub-vertical: for each deal year 2018-2026, the median EV/EBITDA and/or EV/Revenue multiple with middle 50% (25th-75th percentile), deal count n and median deal value, from the open per-year dataset. Only years with at least 10 disclosed deals for a metric are shown; missing years are listed as gaps and never interpolated, so many sub-verticals have few or no years. Use it for 'are multiples rising or falling for X?' questions; use get_valuation_multiples for pooled figures by deal size.

Input Schema

Name	Required	Description	Default
`metric`	No	Optional. Multiple to use: ev_ebitda (enterprise value / EBITDA) or ev_revenue (enterprise value / revenue). Omit to show both where published.
`industry`	Yes	Sub-vertical id from list_industries (e.g. 'hvac', 'dental-practice'), or a plain-English name ('HVAC', 'dentist', 'plumber', 'MSP'); plain names are mapped to the closest tracked category and the answer says which one was used.

Output Schema

Name	Required	Description	Default
`result`	Yes

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.2.0Oct 29, 2026

TDQS

A4.7/5.0

Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Beyond the read-only annotations, the description discloses important behavior: only years with at least 10 disclosed deals per metric appear, missing years are listed as gaps and never interpolated, and many sub-verticals have few or no years. This is exactly the kind of caveat an agent needs before invoking the tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The key scope is front-loaded, and the description is dense with useful information rather than filler. Every sentence contributes either scope, data behavior, caveats, or routing guidance.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

The tool is complex enough to need caveats, and the description covers the year range, threshold behavior, gaps, non-interpolation, and sibling routing. With annotations, full schema coverage, and an output schema already present, nothing important is missing.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, and the schema already documents metric and industry thoroughly, including enum values and plain-English mapping. The description reinforces that only one sub-vertical is used and that metric may show one or both multiples, but it adds little beyond the structured schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description states a specific verb and resource: year-by-year history for one sub-vertical, with named metrics, date range, percentiles, and deal counts. It clearly distinguishes itself from get_valuation_multiples by contrasting per-year trend data with pooled figures by deal size.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It gives an explicit use case ('are multiples rising or falling for X?') and names the alternative tool for pooled figures by deal size. The condition that selects this tool versus get_valuation_multiples is therefore clear and actionable.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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